用线性状态观测器重构交流矢量控制系统中的负载扰动

在异步电动机磁场定向数学模型的基础上,给出了恒磁条件下异步电动机的解耦模型及传动系统的线性状态方程,并提出了重构负载扰动转矩的线性状态观测器。利用重构的负载转矩在矢量控制系统中进行扰动前馈,明显地提高了系统的抗负载扰动能力,从而为进一步提高矢量控制系统的动态性能开辟了一条有效的途径。     

远程公文传输解决方案

以黑龙江省审计厅办公自动化系统为背景,简要说明了公文远程传输的实现内容和方法。内容包括:公文远程传输对于建立办公自动化系统的重要意义;远程传输的功能需求;以及实现远程传输的基本方法。     

一种新型微处理器功能验证

文中介绍一种新型微处理器的验证方法，并对相关的一些验证策略进行深入的讨论。     

Pure perceptual-based sequence learning.

Learning a sequence of target locations when the sequence is uncorrelated with a sequence of responses and target location is not the response dimension (pure perceptual-based sequence learning) was examined. Using probabilistic sequences of target locations, the author shows that such learning can be implicit, is unaffected by distance between target locations, and is mostly limited to first-order transition probabilities. Moreover, the mechanism underlying learning affords processing of information at anticipated target locations and appears to be attention based. Implications for hypotheses of implicit sequence learning are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

模糊聚类在三维地震参数处理中的应用

三维地震参数是一个庞大的三维数据体，能从不同侧面反映储集层的特征。通过对三维地震参数的分析，可以评估油藏表征的参数（沉积相、构造、生长历史、流体饱和度等）。针对传统的聚类方法不能很好地综合考虑各个参数之间的相似程度，提出了用模糊C-均值聚类（fuzzy c-means clustering，简称FCM）对三维地震参数进行处理。从三维地震参数和油藏表征参数之间的关系出发，采用模糊C-均值聚类方法对三维地震参数进行处理，依此评估油藏表征的参数。测试结果表明，模糊C-均值聚类方法能够对三维地震参数进行较为准确的分类，并为储集层的研究提供了很好的依据。     

图像处理中自适应数学形态学的研究

实际图像处理中当视场的变化引起目标变形时,固定大小的形态学算子很难达到较好的处理效果。研究了利用距离变换自适应地调整结构元大小的方法,即根据图像的不同位置来调整结构元素的大小,从而实现图像的形态学运算,并由此推导出了快速计算方法,最后测试了这种新算法的有效性。实验结果表明,该算法取得了较为理想的效果。     

Optimal Locations of Groundwater Extractions in Coastal Aquifers

A regional water supply management model for coastal aquifers was developed. One of its outcomes is the definition of the optimized locations for groundwater withdrawal. Such a tool permits the analysis of alternative plans for groundwater extraction and the sustainable use of water resources in a coastal aquifer subject to saltwater intrusion. The principal components are the evolutionary optimization and the analytical/numerical simulation models. The optimization technique looks for the best well locations taking into consideration the economic results and the satisfaction of the societal water demand. However these two concerns are conditioned by trying to control the saltwater intrusion, i.e., preserving the environmental equilibrium. The simulation model uses the governing mathematical equations for groundwater movement to find the interface between freshwater and saltwater. Because of the non-linearity in the system and the possibility of a jumping interface, a security distance was defined. This is a controlling variable which can be set by the decision makers. The model was applied to a typical case with interesting results. For example, diagrams showing the relationship between the location of the wells and the security distance(s) are of importance to the managers. It was also crucial to have an understanding of the tradeoffs between groundwater withdrawals, positions of the wells from the coast line, and the security distance. The model was also applied to a real case in order to relate the extractions, distances and artificial recharge (not presented in this paper).     

Achievement of specificational information usage with true and false feedback in learning a visual relative-mass discrimination task.

Participants' usage of informational variables in learning visual relative-mass discrimination in collisions was tracked by means of PROBIT correlations. Four groups received feedback that was true or accorded with either of three nonspecificational cue variables. A majority in each group adopted the feedback, but several participants defied the false feedback. Unlike in previous research, the fit to data of the relative-mass invariant could not be bettered by post hoc linear combinations of the cues. Discriminability was lower in the use of the invariant. Analytic complexity was rejected as an explanation for discriminability differences. A "smart mechanism" for pickup of the relative-mass invariant was developed as an extension of G. Johansson's (1950/1994) vector model. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Two-tier architecture for unconstrained handwritten character recognition

In this paper, we propose an approach that combines the unsupervised and supervised learning techniques for unconstrained handwritten numeral recognition. This approach uses the Kohonen self-organizing neural network for data classification in the first stage and the learning vector quantization (LVQ) model in the second stage to improve classification accuracy. The combined architecture performs better than the Kohonen self-organizing map alone. In the proposed approach, the collection of centroids at different phases of training plays a vital role in the performance of the recognition system. Four experiments have been conducted and experimental results show that the collection of centroids in the middle of the training gives high performance in terms of speed and accuracy. The systems developed also resolve the confusion between handwritten numerals.     

模糊C-球壳聚类算法及其在血液细胞图像中的应用

文章从经典的模糊C均值算法开始通过改变其中相似性的度量形式，介绍了一种模糊C球壳聚类（FCSS）算法。在将该算法应用于细胞显微图像半径统计时，采用基于形态学的图像预处理措施，可以获得FCSS算法中有关原型模式的知识，加快收敛速度并避免随机初始化造成的局部极小问题。